Total participants rowing = 21
Basic oral health descriptives (self-report)
Level of Dental caries is based on ICDAS which has 2 scores, level 1 for filling status and level 2 for dental caries:
ICDAS_1 (codes for different filling materials/status), 0, 1 indicate sound/healthy teeth
ICDAS_2 (codes for level of dental caries)
ICDAS_2: 0 (sound), 1 initial visual decay , 2 (distinct change initial ‘caries’), 3/4 moderate decay, 5/6 extensive caries of different extent
NB: Teeth scoring ICDAS_2 >=3 (ie, 3-6) require treatment
FB24 and KBTB files are merged by participant ID
Meals and Snacks recorded separately
For the Rowers.Rmd EDA we report ‘Rowers’ in comparison to all ‘Others’.
We use foodbook_daily_intakes which is the summarised
version of the FB24 data. We further map the Meal into
MealShort by factorising the meals in SNACK and MEAL.
koboData is the KoboToolbox survey data with the
adjustment.
combinedProfiles is joining koboData and
foodbook_daily_intakes
koboProfiles is subset of the koboData with
the following column redefined
combined_icdas_score_2 as the sum of
count_icdas_score_2 above score 3 (scores 3, 4, 5, 6)sport_remap is defined by collapsing the original
column into Rowing Others| score | countSubject |
|---|---|
| 0 | 88 |
| 1 | 29 |
| 2 | 18 |
| 3 | 64 |
| 4 | 36 |
| 6 | 6 |
| 7 | 12 |
| 8 | 5 |
| 96 | 8 |
| 97 | 10 |
| 98 | 25 |
| 99 | 30 |
| score | countSubject |
|---|---|
| 0 | 88 |
| 1 | 6 |
| 2 | 76 |
| 3 | 74 |
| 4 | 45 |
| 5 | 23 |
| 6 | 4 |
## mapping: x = ~last_dental_visit, colour = ~gender, fill = ~gender
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack
## mapping: x = ~describe_health, colour = ~gender, fill = ~gender
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack
## mapping: x = ~pain_12months, colour = ~gender, fill = ~gender
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack
## mapping: x = ~teeth_affect_smiling, colour = ~gender, fill = ~gender
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack
## mapping: x = ~frequency_sweets, colour = ~gender, fill = ~gender
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack
## mapping: x = ~drinks_after_competitions, colour = ~gender, fill = ~gender
## geom_bar: just = 0.5, width = NULL, na.rm = FALSE, orientation = NA
## stat_count: width = NULL, na.rm = FALSE, orientation = NA
## position_stack
## # A tibble: 20 × 5
## combined_icdas_score_2 sport_remap count total percentage
## <dbl> <chr> <int> <int> <dbl>
## 1 0 Others 5 67 0.0746
## 2 1 Others 12 67 0.179
## 3 2 Others 10 67 0.149
## 4 3 Others 5 67 0.0746
## 5 4 Others 8 67 0.119
## 6 5 Others 5 67 0.0746
## 7 6 Others 5 67 0.0746
## 8 7 Others 6 67 0.0896
## 9 8 Others 2 67 0.0299
## 10 9 Others 7 67 0.104
## 11 13 Others 2 67 0.0299
## 12 0 Rowing 4 21 0.190
## 13 1 Rowing 3 21 0.143
## 14 2 Rowing 1 21 0.0476
## 15 3 Rowing 2 21 0.0952
## 16 4 Rowing 1 21 0.0476
## 17 5 Rowing 2 21 0.0952
## 18 6 Rowing 3 21 0.143
## 19 7 Rowing 4 21 0.190
## 20 8 Rowing 1 21 0.0476
Mean intake= in a single meal or snack, mean of what was actually consumed (“average consumption”)
Mean daily intake= sum of total intake/no. of recalls when food actually consumed (if not consumed is not included in denominator)
dentalNutStats function: selected nutrients for dental impact “ENERGY (KCAL)”,“CHO”, “SUGARS”,“STARCH”- Uses Combined profile and fbSubjectIntakeLong: aggregated data by user so that we that we can calcluate mean intake by each participant to give:
total_consumptions=sum(consumption),
max_daily_consumptions=max(consumption), mean_intake = mean(intake),
max_intake = max(intake), sum_intake = sum(intake),
recalls=n_distinct(Recall #)
mean_daily_intake = sum_intake / recalls
## Rows: 13 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): GroupCodeShort
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Warning: Using an external vector in selections was deprecated in tidyselect 1.1.0.
## ℹ Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(dentalNutrients)
##
## # Now:
## data %>% select(all_of(dentalNutrients))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Rows: 13 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): GroupCodeShort
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Rows: 13 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): GroupCodeShort
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Rows: 13 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): GroupCodeShort
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.